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First Semester Computer Science Students’ Academic Performances Analysis by Using Data Mining Classification Algorithms
Published 2014“…The comparative analysis is also conducted to discover the best classification model for prediction. From the experiment, the models develop using Rule Based and Decision Tree algorithm shows the best result compared to the model develop from the Naïve Bayes algorithm. …”
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A Data Mining Approach to Construct Graduates Employability Model in Malaysia
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A data mining approach to construct graduates employability model in Malaysia
Published 2011“…This study is to construct the Graduates Employability Model using classification task in data mining. To achieve it, we use data sourced from the Tracer Study, a web-based survey system from the Ministry of Higher Education, Malaysia (MOHE) for the year 2009. …”
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Predicting students’ STEM academic performance in Malaysian secondary schools using educational data mining
Published 2023“…Four different data mining classification algorithms which are Random Forest, PART, J48 and Naive Bayes will be used on the dataset. …”
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A study of feature selection algorithms for predicting students academic performance
Published 2018“…In EDM, Feature Selection (FS) plays a vital role in improving the quality of prediction models for educational datasets. FS algorithms eliminate unrelated data from the educational repositories and hence increase the performance of classifier accuracy used in different EDM practices to support decision making for educational settings. …”
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A study of feature selection algorithms for predicting students academic performance
Published 2018“…In EDM, Feature Selection (FS) plays a vital role in improving the quality of prediction models for educational datasets. FS algorithms eliminate unrelated data from the educational repositories and hence increase the performance of classifier accuracy used in different EDM practices to support decision making for educational settings. …”
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Comparison of algorithm Support Vector Machine and C4.5 for identification of pests and diseases in chili plants
Published 2019“…The use of data mining algorithms is expected to help in the identification of pests and diseases in chili plants. …”
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Feature selection methods application towards a new dataset based on online student activities / Muhammad Hareez Mohd Zaki ... [et al.]
Published 2023“…The increasing usage of classification algorithms has encouraged researchers to explore many topics including academic-related topics. …”
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Classification models for higher learning scholarship award decisions
Published 2018“…In this study, a data mining approach was used to propose a classification model of scholarship award result determination. …”
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Predicting STEM academic performance in secondary schools: data mining approach
Published 2019“…Three different data mining classification algorithms which are Decision Tree (DT), Artificial Neural Networks (ANN), and Naive Bayes (NB) will be used on the dataset. …”
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Ensemble learning for multidimensional poverty classification
Published 2020“…Analysis of this study showed that Per Capita Income, State, Ethnic, Strata, Religion, Occupation and Education were found to be the most important variables in the classification of poverty at a rate of 99% accuracy confidence using Random Forest algorithm.…”
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A simultaneous spam and phishing attack detection framework for short message service based on text mining approach
Published 2017“…The Phishing Rule-Based algorithm is used to extract SMS Phishing. …”
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DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH
Published 2005“…The project's objective is identifying the available data mining algorithms in data classification and applying new data mining algorithm to perform classification tasks. …”
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Evaluation of data mining classification and clustering techniques for diabetes / Tuba Pala and Ali Yilmaz Camurcu
Published 2014“…The success evaluation of data mining classification algorithms have been realized through the data mining programs Weka and RapidMiner. …”
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An application of predicting student performance using kernel k-means and smooth support vector machine
Published 2012“…In this study, psychometric factors used as predictor variables, thereare Interest, Study Behavior, Engaged Time, Believe, and Family Support.The rulemodel developed using Kernel K-means Clustering and Smooth Support Vector MachineClassification.Both of these techniquesbased on kernel methodsand relativelynew algorithms of data mining techniques, recently received increasingly popularity in machine learning community. …”
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Combining object-based classification and data mining algorithm to classify urban surface materials from worldview-2 satellite image
Published 2014“…In this study, Data Mining was performed using C4.5 algorithm to select the appropriate attributes for object-based classification. …”
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Case Slicing Technique for Feature Selection
Published 2004“…One of the problems addressed by machine learning is data classification. Finding a good classification algorithm is an important component of many data mining projects. …”
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Comparison Performance of Qualitative Bankruptcy Classification based on Data Mining Algorithms
Published 2018“…Knowledge discovery using data mining techniques are commonly applied in bankruptcy classification and prediction. …”
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Data Mining Analysis Of Chronic Kidney Disease (CKD) Level
Published 2022“…Adding the uncertain class the best accuracy obtained was 98.5% using the SMO algorithm. A predictive classification model that determines the accuracy for three classification classes was developed accordingly using the SMO algorithm.…”
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The application of neural network data mining algorithm into mixed pixel classification in geographic information system environment
Published 2007“…Region growing segmentation and radial basis function algorithms are considered a powerful tool to minimize the mixed pixel classification error.…”
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